Study of Human Thermal Comfort for Cyber–Physical Human Centric System in Smart Homes

Fang, Yuan; Lim, Yuto; Ooi, Sian En; Zhou, Chenmian; Tan, Yasuo

doi:10.3390/s20020372

Cited by 29 publications

(5 citation statements)

References 34 publications

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“…In order to avoid the influence of human thermal sensation differences in the experiment, it was necessary to ensure that the subjects were in the thermal comfort range. In [ 30 ], human thermal comfort has been discussed for Cyber-Physical Human-Centric Systems in smart homes. In [ 31 ], the correlation of personal lighting comfort model factors have been analyzed in Cyber-Physical Human-Centric Systems.…”

Section: Experimental Methodologymentioning

confidence: 99%

A Study of the Effects of Different Indoor Lighting Environments on Computer Work Fatigue

Fang

Chang

Cheng-cheng

et al. 2022

IJERPH

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The indoor lighting environment is a key factor affecting human health and safety. In particular, people have been forced to study or work more for long periods of time at home due to the COVID-19 pandemic. In this study, we investigate the influence of physical indoor environmental factors, correlated color temperature (CCT), and illumination on computer work fatigue. We conducted a within-subject experiment consisting of a 10 min-long task test under two different illumination settings (300 lx and 500 lx) and two CCTs (3000 K and 4000 K). Physiological signals, such as electroencephalogram (EEG), electrocardiograph (ECG), and eye movement, were monitored during the test to objectively measure fatigue. The subjective fatigue of eight participants was evaluated based on a questionnaire conducted after completing the test. The error rate of the task test was taken as the key factor representing the working performance. Through the analysis of the subjective and objective results, computer work fatigue was found to be significantly impacted by changes in the lighting environment, where human fatigue was negatively correlated with illumination and CCT. Improving the illumination and CCT of the work environment, within the scope of this study, helped to decrease the fatigue degree—that is, the fatigue degree was the lowest under the 4000 K + 500 lx environment, while it was relatively high at 3000 K + 300 lx. Under indoor environment conditions, the CCT factor was found to have the greatest effect on computer work fatigue, followed by illumination. The presented results are expected to be a valuable reference for improving the satisfaction associated with the lighting environment and to serve as guidance for researchers and reviewers conducting similar research.

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Section: Experimental Methodologymentioning

confidence: 99%

A Study of the Effects of Different Indoor Lighting Environments on Computer Work Fatigue

Fang

Chang

Cheng-cheng

et al. 2022

IJERPH

Self Cite

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“…They report energy consumption, classifying it by type source or home appliance use [ 14 , 15 ]. They used to prevent damages to the household or their occupants [ 16 , 17 ], increasing levels of comfort of the occupants/users [ 18 ], and currently converting all the household appliances into reactive elements the smart home [ 19 ].…”

Section: Related Workmentioning

confidence: 99%

Design and Implementation of the E-Switch for a Smart Home

García-Vázquez

Guerrero-Osuna

Ornelas-Vargas

et al. 2021

Sensors

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As the development of systems in smart homes is increasing, it is of ever-increasing importance to have data, which artificial intelligence methods and techniques can apply to recognize activities and patterns or to detect anomalies, with the aim of reducing energy consumption in the main home domestic services, and to offer users an alternative in the management of these resources. This paper describes the design and implementation of a platform based on the internet of things and a cloud environment that allows the user to remotely control and monitor Wi-Fi wireless e-switch in a home through a mobile application. This platform is intended to represent the first step in transforming a home into a smart home, and it allows the collection and storage of the e-switch information, which can be used for further processing and analysis.

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“…The "Aware Home" prototype presented in (31) was intended as a living laboratory for research in ubiquitous computing for everyday activities and included the following spaces in the house: two identical and independent living spaces, consisting of two bedrooms, two bathrooms, one office, kitchen, dining room, living room, and laundry room. One of the living spaces was intended to be where the person would spend most of the time during the duration of the study.…”

Section: Traditional Smart Home Approachesmentioning

confidence: 99%

Design and Implementation of a Smart Home in a Box to Monitor the Wellbeing of Residents With Dementia in Care Homes

García-Constantino

Orr

Synnott

et al. 2021

Front. Digit. Health

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There is a global challenge related to the increasing number of People with Dementia (PwD) and the diminishing capacity of governments, health systems, and caregivers to provide the best care for them. Cost-effective technology solutions that enable and ensure a good quality of life for PwD via monitoring and interventions have been investigated comprehensively in the literature. The objective of this study was to investigate the challenges with the design and deployment of a Smart Home In a Box (SHIB) approach to monitoring PwD wellbeing within a care home. This could then support future SHIB implementations to have an adequate and prompt deployment allowing research to focus on the data collection and analysis aspects. An important consideration was that most care homes do not have the appropriate infrastructure for installing and using ambient sensors. The SHIB was evaluated via installation in the rooms of PwD with varying degrees of dementia at Kirk House Care Home in Belfast. Sensors from the SHIB were installed to test their capabilities for detecting Activities of Daily Living (ADLs). The sensors used were: (i) thermal sensors, (ii) contact sensors, (iii) Passive Infrared (PIR) sensors, and (iv) audio level sensors. Data from the sensors were collected, stored, and handled using a ‘SensorCentral’ data platform. The results of this study highlight challenges and opportunities that should be considered when designing and implementing a SHIB approach in a dementia care home. Lessons learned from this investigation are presented in addition to recommendations that could support monitoring the wellbeing of PwD. The main findings of this study are: (i) most care home buildings were not originally designed to appropriately install ambient sensors, and (ii) installation of SHIB sensors should be adapted depending on the specific case of the care home where they will be installed. It was acknowledged that in addition to care homes, the homes of PwD were also not designed for an appropriate integration with ambient sensors. This study provided the community with useful lessons, that will continue to be applied to improve future implementations of the SHIB approach.

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Study of Human Thermal Comfort for Cyber–Physical Human Centric System in Smart Homes

Cited by 29 publications

References 34 publications

A Study of the Effects of Different Indoor Lighting Environments on Computer Work Fatigue

A Study of the Effects of Different Indoor Lighting Environments on Computer Work Fatigue

Design and Implementation of the E-Switch for a Smart Home

Design and Implementation of a Smart Home in a Box to Monitor the Wellbeing of Residents With Dementia in Care Homes

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